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Cardiometabolic–Resting-State Functional Connectivity Associations Differ by Age and Menopausal Status in Middle-Aged Females

This study demonstrates that menopause status significantly differentiates how cardiometabolic risk factors, such as systolic blood pressure and total cholesterol, relate to resting-state functional connectivity patterns in middle-aged females, with specific associations varying by menopausal stage despite neither pattern predicting spatial memory performance.

Original authors: Julia Kearley, Charana Rajagopal, Sophia LoParco, Millie R. Bhaskara, Lucina Q. Uddin, Bratislav Misic, Gillian Einstein, Louise Pilote, M. Natasha Rajah

Published 2026-07-13

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Julia Kearley, Charana Rajagopal, Sophia LoParco, Millie R. Bhaskara, Lucina Q. Uddin, Bratislav Misic, Gillian Einstein, Louise Pilote, M. Natasha Rajah

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine your brain as a bustling city with millions of roads connecting different neighborhoods. Some roads are for high-speed traffic (attention), others are for daydreaming (memory), and some are for the city's emotional core. Scientists call these "resting-state functional connectivity" patterns, or simply how well the neighborhoods talk to each other when you're just chilling.

This study looked at 83 women between the ages of 40 and 65 to see how their "heart-health" stats (like blood pressure and cholesterol) affect these brain roads. But here's the twist: the researchers split the group into two teams based on a major biological milestone—menopause. One team was still pre-menopause (the "before" team), and the other was post-menopause (the "after" team). They wanted to know: Does the map of how heart health connects to brain roads change when a woman transitions from one team to the other?

The Big Discovery: Two Different Rulebooks

The researchers found that the answer is a resounding yes. The rules of the game are totally different depending on which team you are on. They used a special math tool (called B-PLS) to find two main patterns, or "rulebooks," that explained how heart health and brain roads interact.

Rulebook #1: The Age and Blood Pressure Connection
This rulebook is all about age and systolic blood pressure (the top number in a blood pressure reading).

For the "Before" Team (Premenopausal): As these women got older, their brain roads in the emotional and memory neighborhoods (the limbic-hippocampal network) and the daydreaming neighborhood (the Default Mode Network) actually got more connected. Interestingly, higher blood pressure was also linked to this extra connection.
For the "After" Team (Postmenopausal): The script flipped! As these women got older, those same brain roads got less connected. In this group, age was the main driver, but blood pressure didn't seem to play a role in this specific pattern.
The Takeaway: It's like a seesaw. In the "before" group, getting older and having higher blood pressure pushed the brain roads together. In the "after" group, getting older pushed them apart. The study suggests that menopause status changes how age and blood pressure influence these specific brain connections.

Rulebook #2: The Cholesterol Connection
This rulebook is all about total cholesterol and is completely independent of age.

For the "Before" Team: Higher total cholesterol was linked to fewer connections in the "Dorsal Attention Network" (the brain's focus team) and its connections to other areas like the visual and motor neighborhoods.
For the "After" Team: The opposite happened! Higher total cholesterol was linked to more connections in these same focus networks.
The Takeaway: Cholesterol acts like a different kind of traffic signal depending on your team. Before menopause, high cholesterol seems to slow down the focus roads. After menopause, high cholesterol seems to speed them up (or at least, the connections look different). The researchers suggest this might be because the body's hormonal environment changes so much during menopause that cholesterol means something different biologically before and after the transition.

What the Study Explicitly Says It Did NOT Find

It is just as important to know what this study didn't find.

No Memory Link: The researchers tested if these specific brain road patterns predicted how well the women did on a memory game (remembering where a face was on a screen). The answer? Nothing. The study explicitly states that neither of these brain patterns predicted memory performance. So, while we know heart health and menopause change the brain's wiring, this study does not prove that these specific changes cause memory problems right now.
No "One Size Fits All": The study argues against the idea that we can just look at a woman's age and heart health and assume the brain effects are the same for everyone. Menopause status is a critical factor that changes the equation.

How Sure Are We?

The researchers are confident they measured these differences in the brain's wiring and found them to be statistically significant. They used rigorous methods to ensure the patterns weren't just random noise.

They measured that postmenopausal women in their group were older, had higher blood pressure, and higher total cholesterol than the premenopausal women.
They measured that the brain connection patterns differed significantly between the two groups.
However, because this was a "snapshot" study (they looked at everyone at one time), they suggest that menopause causes these changes, but they cannot prove it with 100% certainty without watching the same women over many years. They note that other factors, like being born in a different era (cohort effects), could also play a role, though the hormonal changes of menopause are the most likely culprit.

The Bottom Line

Think of the brain as a city. This study suggests that the "construction crew" (heart health factors like blood pressure and cholesterol) builds and maintains the roads differently depending on whether the city is in its "pre-menopause" or "post-menopause" phase.

Blood pressure seems to tighten the emotional roads in younger women but loosen them in older women.
Cholesterol seems to clog the focus roads in younger women but open them up in older women.

The study concludes that to understand brain health in middle-aged women, we can't just look at age or heart health alone; we have to know where they are on the menopause timeline, because that timeline changes the rules of the road entirely.

Technical Summary: Cardiometabolic–Resting-State Functional Connectivity Associations Differ by Age and Menopausal Status in Middle-Aged Females

Problem Statement
Midlife represents a critical window where demographic and modifiable cardiometabolic factors shape later-life cognitive and brain trajectories. While cardiometabolic risk factors (e.g., blood pressure, lipid profiles) are known to influence brain health and resting-state functional connectivity (rsFC), the specific role of menopausal status in modulating these associations remains underexplored. Existing literature suggests that the transition from pre- to post-menopause involves significant shifts in ovarian hormones, lipid profiles, and vascular function, yet prior work has not directly compared how menopausal status influences the multivariate associations between cardiometabolic risk factors and whole-brain rsFC in middle-aged females. This study addresses this gap by examining whether the covariance between midlife cardiometabolic/demographic variables and rsFC differs between premenopausal and postmenopausal women.

Methodology
The study utilized data from 83 cognitively unimpaired middle-aged females (40–65 years) from the Brain Health at Midlife and Menopause (BHAMM) cohort. Participants were classified as premenopausal ( $n=42$ ) or postmenopausal ( $n=41$ ) based on the Stages of Reproductive Aging Workshop (STRAW) +10 criteria, confirmed by plasma estradiol (E2) and follicle-stimulating hormone (FSH) levels. Exclusion criteria included current menopausal hormone therapy (MHT), hormonal birth control (for postmenopausal women), and conditions affecting brain structure or function.

Data Acquisition: Participants underwent 10 minutes of eyes-open resting-state fMRI (rs-fMRI) on a 3T Siemens Prisma-FIT scanner. Cardiometabolic variables included systolic blood pressure (SBP), total cholesterol, body mass index (BMI), and physical activity levels. Demographic variables included age and years of education.
Preprocessing: fMRI data were processed using fMRIPrep (v20.2.0) and a custom pipeline involving motion censoring, CompCor, and ICA-AROMA denoising.
Connectivity Estimation: RsFC was estimated using a 204-region of interest (ROI) approach (200 cortical ROIs from the Schaefer 2018 atlas and 4 hippocampal ROIs), resulting in 204 $\times$ 204 connectivity matrices.
Statistical Analysis: A two-group Behavioral Partial Least Squares (B-PLS) analysis was employed to identify latent variables (LVs) capturing maximal covariance between the whole-brain rsFC matrices and the behavioral variables (age, education, SBP, total cholesterol). Variables showing significant group differences were retained for the behavioral matrix. Significance was assessed via permutation testing (1,000 permutations), and reliability via bootstrap resampling (500 bootstraps). Sensitivity analyses using reduced-block B-PLS were conducted to isolate the contributions of individual behavioral variables.
Memory Correlation: The study examined whether the identified rsFC patterns predicted performance on a spatial context episodic memory task (Correct Source and Correct Rejection rates) using linear regression within each group.

Key Results
Group comparisons revealed that postmenopausal females were significantly older, had fewer years of education, higher SBP, and higher total cholesterol compared to premenopausal females. BMI and physical activity did not differ significantly.

The B-PLS analysis identified two significant latent variables:

Latent Variable 1 (LV1): This pattern captured menopause group differences in the association between age, SBP, and rsFC.
- Networks: Primarily involved the limbic+hippocampal network, the Default Mode Network (DMN), and the visual network.
- Associations: In premenopausal females, older age and higher SBP were associated with increased within-network connectivity in the limbic+hippocampal and visual networks, and increased between-network connectivity between the limbic+hippocampal and DMN. Conversely, in postmenopausal females, older age was associated with decreased connectivity in these same patterns. SBP was not significantly associated with this pattern in postmenopausal females.
- Drivers: Sensitivity analyses indicated that age and SBP were the dominant contributors to this pattern.
Latent Variable 2 (LV2): This pattern captured menopause group differences in the association between total cholesterol and rsFC, independent of age.
- Networks: Primarily involved the Dorsal Attention Network (DAN), somatomotor network, and visual network.
- Associations: In premenopausal females, higher total cholesterol was associated with reduced within-network connectivity in the DAN, somatomotor, and visual networks, and reduced between-network connectivity involving the DAN. In postmenopausal females, higher total cholesterol was associated with increased connectivity in these same patterns.
- Drivers: Sensitivity analyses confirmed that total cholesterol was the dominant contributor to this pattern, with minimal contribution from age or SBP.

Memory Performance: Neither LV1 nor LV2 brain scores significantly predicted spatial context memory performance (Correct Source or Correct Rejection rates) in either premenopausal or postmenopausal groups.

Significance and Claims
The authors claim that menopause status provides a critical context for differentiating how chronological and reproductive age contribute to the heterogeneity of cardiometabolic-rsFC associations in middle-aged females. Specifically:

Interaction of Age and Menopause: The study demonstrates that the relationship between age/SBP and limbic/DMN connectivity is inverted between pre- and post-menopausal women, suggesting a non-linear or "inverted-U" association modulated by reproductive status.
Menopause-Specific Lipid Effects: The association between total cholesterol and DAN connectivity differs fundamentally by menopausal status and is independent of chronological age. This suggests that peripheral total cholesterol may index different biological states (systemic lipid-vascular environments) before and after menopause due to shifts in hormonal and vascular contexts.
Vascular-Metabolic Context: The findings support the view that BOLD-derived functional connectivity is shaped by neurovascular coupling and metabolic physiology, which are altered by menopausal endocrine aging. Therefore, cardiometabolic factors may relate to rsFC patterns differently depending on menopausal status.

The paper concludes that these findings highlight the necessity of considering menopausal status when studying midlife brain health, as it may explain variability in how cardiometabolic risk factors influence brain network organization. The authors note that while these patterns were not linked to concurrent memory performance in this cross-sectional sample, longitudinal follow-up is required to determine if these rsFC patterns predict future cognitive decline.

The Big Discovery: Two Different Rulebooks

What the Study Explicitly Says It Did NOT Find

How Sure Are We?

The Bottom Line

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